Online Algorithms for Cost-Effective Cloud Selection with Multiple Demands

Abstract

Cloud computing provides high flexibility for users by offering diverse cloud instances with various leasing periods and prices. Depending on the amount and duration of workload, a user can flexibly choose proper cloud instances to meet her demands. An intrinsic challenge facing the user is which classes of clouds and how many of them to purchase in order to meet her unpredictable demands at minimum cost. We consider an online problem deciding cost-effectively cloud classes and amount of clouds to meet dynamic multiple demands among many cloud classes when no future information of demands is available. We propose two online algorithms achieving O(M) and O(log M + log d_max) competitive ratios where M is the number of available cloud classes and d_max is the maximum demand of a given demand sequence.